Reconstruction-error-based learning for continuous emotion recognition in speech

Jing Han, Zixing Zhang, Fabien Ringeval, Bjorn Schuller

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

31 Scopus citations

Abstract

To advance the performance of continuous emotion recognition from speech, we introduce a reconstruction-error-based (RE-based) learning framework with memory-enhanced Recurrent Neural Networks (RNN). In the framework, two successive RNN models are adopted, where the first model is used as an autoencoder for reconstructing the original features, and the second is employed to perform emotion prediction. The RE of the original features is used as a complementary descriptor, which is merged with the original features and fed to the second model. The assumption of this framework is that the system has the ability to learn its 'drawback' which is expressed by the RE. Experimental results on the RECOLA database show that the proposed framework significantly outperforms the baseline systems without any RE information in terms of Concordance Correlation Coefficient (.729 vs.710 for arousal,.360 vs.237 for valence), and also significantly overcomes other state-of-the-art methods.

Original languageEnglish
Title of host publication2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2367-2371
Number of pages5
ISBN (Electronic)9781509041176
DOIs
StatePublished - 16 Jun 2017
Externally publishedYes
Event2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - New Orleans, United States
Duration: 5 Mar 20179 Mar 2017

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Conference

Conference2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017
Country/TerritoryUnited States
CityNew Orleans
Period5/03/179/03/17

Keywords

  • Continuous emotion recognition
  • bidirectional long short-term memory
  • reconstruction error

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